Stage 3: Production Security - Complete Defense¶
Status: 🚧 In Development (Planned February 2026)
Security Rating: 10/10 (Target)
Attack Success Rate: 0% (Target)
Purpose: Demonstrate production-grade comprehensive security
🎯 Overview¶
Stage 3 implements production-grade security with comprehensive defense in depth. All Stage 1 and Stage 2 attacks are completely blocked, demonstrating what secure multi-agent systems require.
What You'll Learn¶
- How to implement zero-trust architecture
- How behavioral analysis detects anomalies
- How automated threat response works
- How to achieve production-level security
- Why comprehensive defense beats partial security
📊 Security Enhancements Over Stage 2¶
1. Deep Recursive Validation ✅¶
Fixes: VULN-S2-002 (Deep-Nested Data Exfiltration)
class DeepValidator:
MAX_DEPTH = 5
MAX_DICT_SIZE = 100
MAX_LIST_SIZE = 50
MAX_STRING_SIZE = 1000
def deep_validate(self, data, depth=0):
"""Recursively validate ALL nested structures"""
if depth > self.MAX_DEPTH:
return False, "Max nesting depth exceeded"
if isinstance(data, dict):
if len(data) > self.MAX_DICT_SIZE:
return False, "Dictionary too large"
for key, value in data.items():
# Validate at EVERY level
is_valid, error = self.deep_validate(value, depth + 1)
if not is_valid:
return False, error
# Checks patterns at ALL levels
return True, "Valid"
Result: ❌ Deep-nested exfiltration BLOCKED
2. Nonce-Based Replay Protection ✅¶
Fixes: VULN-S2-003 (Token Replay Attacks)
class NonceValidator:
def __init__(self, redis_client):
self.redis = redis_client
self.window = 60 # seconds
def validate(self, nonce, timestamp):
"""Prevent message replay"""
# Check nonce hasn't been used
if self.redis.get(f"nonce:{nonce}"):
return False, "Nonce already used (replay detected)"
# Verify timestamp within window
if abs(time.time() - timestamp) > self.window:
return False, "Timestamp outside valid window"
# Store nonce for window duration
self.redis.setex(f"nonce:{nonce}", self.window, "1")
return True, "Valid"
Required in All Messages:
message = {
"type": "status_update",
"nonce": secrets.token_hex(16), # Required!
"timestamp": time.time(), # Required!
"signature": hmac_sign(...), # Required!
...
}
Result: ❌ Token replay BLOCKED (nonces prevent reuse)
3. Role Verification Workflow ✅¶
Fixes: VULN-S2-001 (Role Escalation)
class RoleVerifier:
def request_role(self, agent_id, requested_role):
"""Multi-step role elevation"""
# Step 1: Create pending request
request_id = create_role_request(agent_id, requested_role)
# Step 2: Verify against external identity
if not verify_external_identity(agent_id):
return False, "Identity verification failed"
# Step 3: Require admin approval
notify_admins_for_approval(request_id)
# Step 4: Audit trail
audit_log("role_request", agent_id, requested_role)
return request_id
def approve_role(self, admin_id, request_id):
"""Admin must explicitly approve"""
# Verify admin authority
if not has_admin_role(admin_id):
return False, "Not authorized to approve roles"
# Grant role
grant_role(request.agent_id, request.role)
# Audit
audit_log("role_granted", request.agent_id, request.role, admin_id)
Result: ❌ Self-granted admin roles BLOCKED
4. Behavioral Analysis & Auto-Quarantine ✅¶
Fixes: VULN-S2-004 (Legitimate API Abuse)
class BehaviorMonitor:
def analyze_action(self, agent_id, action, context):
"""Real-time anomaly detection"""
risk_score = 0
# Track action rate
rate = self.action_tracker.get_rate(agent_id, action, window=60)
if rate > NORMAL_THRESHOLD:
risk_score += 30 # Unusual volume
# Detect mass operations
if action == "update_task":
recent_updates = self.count_recent_updates(agent_id, window=60)
if recent_updates > 10:
risk_score += 40 # Mass modification pattern
# Check time patterns
if self.is_unusual_time(current_time):
risk_score += 20 # Activity at odd hours
# Analyze target diversity
if self.targets_multiple_agents(agent_id, context):
risk_score += 30 # Accessing many agents' data
# AUTOMATED RESPONSE
if risk_score >= QUARANTINE_THRESHOLD:
self.quarantine_agent(agent_id, reason="Anomalous behavior")
alert_admin(f"Agent {agent_id} quarantined: risk={risk_score}")
audit_log("auto_quarantine", agent_id, risk_score)
return False, "Agent quarantined"
return True, f"Risk score: {risk_score}"
Quarantine Actions: - Revoke all active tokens - Block new operations - Freeze current tasks - Admin notification - Require manual review
Result: ❌ API abuse DETECTED and BLOCKED automatically
5. Asymmetric Cryptography (RS256) ✅¶
Enhancement: Stronger authentication than Stage 2
class KeyManager:
def __init__(self):
# Generate RSA 2048-bit keypair
self.private_key = rsa.generate_private_key(
public_exponent=65537,
key_size=2048
)
self.public_key = self.private_key.public_key()
def sign_token(self, payload):
"""Sign JWT with private key (RS256)"""
return jwt.encode(
payload,
self.private_key,
algorithm="RS256"
)
def verify_token(self, token):
"""Verify with public key"""
return jwt.decode(
token,
self.public_key,
algorithms=["RS256"]
)
Benefits over Stage 2 HS256: - Public key can be distributed safely - Private key never leaves auth server - More resistant to key compromise - Industry standard for distributed systems
6. State Encryption (AES-256-GCM) ✅¶
Enhancement: Protect data at rest
class StateEncryption:
def encrypt_task(self, task_data, key):
"""Encrypt task with AES-256-GCM"""
# Generate random IV
iv = os.urandom(12)
# Encrypt with authentication
cipher = Cipher(
algorithms.AES(key),
modes.GCM(iv)
)
encryptor = cipher.encryptor()
plaintext = json.dumps(task_data).encode()
ciphertext = encryptor.update(plaintext) + encryptor.finalize()
return {
"iv": base64.b64encode(iv),
"ciphertext": base64.b64encode(ciphertext),
"tag": base64.b64encode(encryptor.tag)
}
def decrypt_task(self, encrypted_data, key):
"""Decrypt and verify integrity"""
# Verify authentication tag first
# Then decrypt
# Any tampering = decryption fails
Protected Data: - All task data at rest - Session state - Sensitive details - Audit logs (with HMAC)
7. Comprehensive Audit System ✅¶
Enhancement: Tamper-evident logging
class AuditLogger:
def log_event(self, event_type, agent_id, details):
"""Integrity-protected logging"""
entry = {
"timestamp": time.time(),
"event_type": event_type,
"agent_id": agent_id,
"details": details,
"sequence": self.get_next_sequence()
}
# Sign with HMAC for integrity
entry["signature"] = hmac.new(
self.audit_key,
json.dumps(entry).encode(),
hashlib.sha256
).hexdigest()
# Store in tamper-evident log
self.log_store.append(entry)
# Real-time monitoring
if is_security_event(event_type):
alert_security_team(entry)
Logged Events: - All authentication attempts - All permission checks - All data access - All modifications - All anomalies detected - All quarantine actions
🛡️ Attack Prevention Matrix¶
| Attack | Stage 1 | Stage 2 | Stage 3 | Prevention Method |
|---|---|---|---|---|
| Anonymous Access | ✅ 100% | ❌ 0% | ❌ 0% | Already blocked (JWT) |
| Simple Spoofing | ✅ 100% | ❌ 0% | ❌ 0% | Already blocked (JWT) |
| Malformed Messages | ✅ 100% | ❌ 0% | ❌ 0% | Already blocked (schema) |
| Role Escalation | ✅ 100% | ✅ 100% | ❌ 0% | Role verification workflow |
| Deep-Nested Exfil | ✅ 100% | ✅ 100% | ❌ 0% | Recursive deep validation |
| Token Replay | N/A | ✅ 100% | ❌ 0% | Nonce + request signing |
| API Abuse | ✅ 100% | ✅ 100% | ❌ 0% | Behavioral analysis + quarantine |
| Overall Success | 100% | 45% | 0% | Comprehensive defense |
✅ = Attack succeeds
❌ = Attack blocked
📈 Security Comparison¶
Stage 1 vs Stage 2 vs Stage 3¶
| Aspect | Stage 1 | Stage 2 | Stage 3 |
|---|---|---|---|
| Authentication | ❌ None | ✅ JWT (HS256) | ✅ JWT (RS256) + MFA |
| Authorization | ❌ None | ⚠️ Basic RBAC | ✅ RBAC + Capabilities |
| Input Validation | ❌ None | ⚠️ Top-level only | ✅ Deep recursive |
| Replay Protection | ❌ None | ❌ None | ✅ Nonce-based |
| Behavioral Analysis | ❌ None | ❌ None | ✅ Real-time monitoring |
| Encryption | ❌ None | ❌ None | ✅ AES-256-GCM |
| Audit Logging | ❌ None | ⚠️ Basic | ✅ HMAC-protected |
| Automated Response | ❌ None | ❌ None | ✅ Auto-quarantine |
| Attack Success Rate | 100% | 45% | 0% |
| Security Rating | 0/10 | 4/10 | 10/10 |
💻 Code Structure (Planned)¶
stage3_secure/
├── README.md
├── auth/
│ ├── auth_manager.py # RS256 + MFA
│ ├── key_manager.py # RSA keypair management
│ ├── nonce_validator.py # Replay protection
│ └── mfa_manager.py # TOTP-based MFA
├── security/
│ ├── permission_manager.py # Enhanced RBAC
│ ├── deep_validator.py # Recursive validation
│ ├── role_verifier.py # Approval workflow
│ ├── behavior_monitor.py # Anomaly detection
│ └── quarantine_manager.py # Automated response
├── core/
│ ├── protocol.py # Nonce-enabled messages
│ ├── task_queue.py # Encrypted storage
│ ├── project_manager.py # Full integration
│ ├── state_encryption.py # AES-256-GCM
│ └── audit_logger.py # HMAC-protected logs
├── agents/
│ ├── malicious_worker.py # Shows attacks FAIL
│ └── legitimate_worker.py # Proper secure usage
└── requirements.txt # redis, cryptography
Estimated Lines: ~4,500 code + 1,500 docs
🎓 Learning Objectives¶
Production Security Patterns¶
- Understand zero-trust architecture
- Implement behavioral analysis
- Design automated threat response
- Apply defense in depth
- Achieve security completeness
Advanced Cryptography¶
- RSA asymmetric encryption
- AES-256-GCM authenticated encryption
- HMAC message authentication
- Nonce-based replay prevention
- Secure key management
Enterprise Requirements¶
- Compliance logging (GDPR, HIPAA)
- Incident response automation
- Audit trail integrity
- High availability security
- Performance at scale
🚀 Development Status¶
Current Phase: Planning Complete ✅
Timeline: - Planning: ✅ Complete (January 2026) - Implementation: 🚧 Starting (January-February 2026) - Testing: 📋 Planned (February 2026) - Documentation: 📋 Planned (February 2026) - Release: 🎯 February 2026
Follow Progress: - GitHub Project Board - Implementation Plan
🔄 Migration from Stage 2¶
For organizations using Stage 2 patterns:
Priority 1: Add Nonce Protection (Week 1)¶
- Implement NonceValidator
- Update message protocol
- Deploy Redis for nonce storage
Priority 2: Deep Validation (Week 2)¶
- Implement DeepValidator
- Replace shallow validator
- Test with nested payloads
Priority 3: Behavioral Monitoring (Week 3)¶
- Implement BehaviorMonitor
- Configure thresholds
- Test quarantine workflow
Priority 4: Role Verification (Week 4)¶
- Implement approval workflow
- Migrate existing roles
- Document process
Total Migration: 4-6 weeks estimated
🎯 Performance Requirements¶
Latency Targets: - Authentication: <50ms per request - Validation: <30ms per message - Behavioral analysis: <20ms per action - Encryption: <40ms per task
Total Overhead: <100ms (acceptable for production)
Scalability: - Concurrent agents: 100+ - Messages/second: 1,000+ - Task queue: 10,000+ tasks - Audit log: 1M+ entries
📚 Related Documentation¶
Prerequisites¶
Deep Dives¶
Standards & Compliance¶
💡 Key Takeaways¶
Why Stage 3 Succeeds¶
Comprehensive Defense: - ✅ Every layer complete - ✅ No gaps for bypass - ✅ Multiple overlapping controls - ✅ Automated threat response
Zero-Trust Principle: - ✅ Verify everything - ✅ Trust nothing by default - ✅ Continuous validation - ✅ Least privilege
Production Quality: - ✅ Industry standards (OWASP, NIST) - ✅ Compliance ready (GDPR, HIPAA) - ✅ Performance acceptable - ✅ Maintainable and scalable
The Complete Journey¶
Stage 1: "Why security matters" → 100% attack success
Stage 2: "Why partial fails" → 45% attack success
Stage 3: "How comprehensive succeeds" → 0% attack success
Final Lesson: Security requires comprehensive, multi-layered defense with continuous monitoring and automated response.
🔔 Get Notified¶
Want to know when Stage 3 is released?
- ⭐ Star the repository
- 👀 Watch for releases
- 📧 Join the mailing list
- 💬 Follow discussions
🤝 Contributing¶
Stage 3 development is collaborative! Help wanted:
- Security review of implementations
- Performance testing
- Documentation improvements
- Attack scenario development
- Use case contributions
See CONTRIBUTING.md
📞 Questions?¶
- Repository: GitHub
- Maintainer: Robert Fischer (robert@fischer3.net)
- Discussions: GitHub Discussions
Last Updated: January 2026
Status: 🚧 In Development
Expected Release: February 2026
License: MIT (Educational Use)